It has proven problematic to accurately and automatically identify facial expressions in digital images. Approximately 30% of facial images are images, such as snapshots, representing faces which have various facial expressions. When a conventional face classification apparatus is used to detect faces in general images, the accuracy in detection is lower compared with images which have substantially the same facial expressions. Therefore, there is a problem that the face classification apparatus of prior art schemes cannot accurately detect facial expressions and specific facial expressions such as smiles, frowns, etc.